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A 3D digital scene contains many components: lights, materials and geometries, interacting to reach the desired appearance. Staging such a scene is time-consuming and requires both artistic and technical skills. In this work, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-07-10 Kai Yan , Fujun Luan , MiloŠ HaŠAn , Thibault Groueix , Valentin Deschaintre , Shuang Zhao

This paper proposes a novel learning based high-dynamic-range (HDR) reconstruction method using a polarization camera. We utilize a previous observation that polarization filters with different orientations can attenuate natural light…

Image and Video Processing · Electrical Eng. & Systems 2022-03-29 Juiwen Ting , Moein Shakeri , Hong Zhang

Physics-based differentiable rendering (PBDR) has become an efficient method in computer vision, graphics, and machine learning for addressing an array of inverse problems. PBDR allows patterns to be generated from perceptions which can be…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Preetish Kakkar , Srijani Mukherjee , Hariharan Ragothaman , Vishal Mehta

This paper introduces a learnable Deformable Hypothesis Sampler (DeformSampler) to address the challenging issue of noisy depth estimation for accurate PatchMatch Multi-View Stereo (MVS). We observe that the heuristic depth hypothesis…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Hongjie Li , Yao Guo , Xianwei Zheng , Hanjiang Xiong

We present the design of a productionized end-to-end stereo depth sensing system that does pre-processing, online stereo rectification, and stereo depth estimation with a fallback to monocular depth estimation when rectification is…

Capturing the 3D geometry of transparent objects is a challenging task, ill-suited for general-purpose scanning and reconstruction techniques, since these cannot handle specular light transport phenomena. Existing state-of-the-art methods,…

Graphics · Computer Science 2020-09-22 Jiahui Lyu , Bojian Wu , Dani Lischinski , Daniel Cohen-Or , Hui Huang

We present a differentiable framework to adaptively compute 4D illumination conditions with respect to an object, for efficient, high-quality simultaneous acquisition of its shape and reflectance, with a unified spatial-angular structured…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Huakeng Ding , Yaowen Chen , Kun Zhou , Hongzhi Wu

We report the application of machine learning to smartphone based colorimetric detection of pH values. The strip images were used as the training set for Least Squares-Support Vector Machine (LS-SVM) classifier algorithms that were able to…

Computer Vision and Pattern Recognition · Computer Science 2017-11-01 Ali Y. Mutlu , Volkan Kılıç , Gizem K. Özdemir , Abdullah Bayram , Nesrin Horzum , Mehmet E. Solmaz

Snapshot hyperspectral imaging systems acquire spectral data cubes through compressed sensing. Recently, diffractive snapshot spectral imaging (DSSI) methods have attracted significant attention. While various optical designs and…

Image and Video Processing · Electrical Eng. & Systems 2025-07-08 Zhengyue Zhuge , Jiahui Xu , Shiqi Chen , Hao Xu , Yueting Chen , Zhihai Xu , Huajun Feng

We introduce Focal Split, a handheld, snapshot depth camera with fully onboard power and computing based on depth-from-differential-defocus (DfDD). Focal Split is passive, avoiding power consumption of light sources. Its achromatic optical…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Junjie Luo , John Mamish , Alan Fu , Thomas Concannon , Josiah Hester , Emma Alexander , Qi Guo

Intelligent reflecting surface (IRS) has been recognized as a powerful technology for boosting communication performance. To reduce manufacturing and control costs, it is preferable to consider discrete phase shifts (DPSs) for IRS, which…

Information Theory · Computer Science 2023-11-07 Guojie Hu , Qingqing Wu , Dognhui Xu , Kui Xu , Jiangbo Si , Yunlong Cai , Naofal Al-Dhahir

Image deep features extracted by pre-trained networks are known to contain rich and informative representations. In this paper, we present Deep Degradation Response (DDR), a method to quantify changes in image deep features under varying…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Juncheng Wu , Zhangkai Ni , Hanli Wang , Wenhan Yang , Yuyin Zhou , Shiqi Wang

Existing vision systems for autonomous driving or robots are sensitive to waterdrops adhered to windows or camera lenses. Most recent waterdrop removal approaches take a single image as input and often fail to recover the missing content…

Computer Vision and Pattern Recognition · Computer Science 2021-08-10 Zifan Shi , Na Fan , Dit-Yan Yeung , Qifeng Chen

Differentiable rendering is an essential operation in modern vision, allowing inverse graphics approaches to 3D understanding to be utilized in modern machine learning frameworks. Explicit shape representations (voxels, point clouds, or…

Computer Vision and Pattern Recognition · Computer Science 2021-12-13 Tristan Aumentado-Armstrong , Stavros Tsogkas , Sven Dickinson , Allan Jepson

This paper introduces a versatile paradigm for integrating multi-view reflectance (optional) and normal maps acquired through photometric stereo. Our approach employs a pixel-wise joint re-parameterization of reflectance and normal,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Baptiste Brument , Robin Bruneau , Yvain Quéau , Jean Mélou , François Bernard Lauze , Jean-Denis , Jean-Denis Durou , Lilian Calvet

Depth position highly affects lens distortion, especially in close-range photography, which limits the measurement accuracy of existing stereo vision systems. Moreover, traditional depth-dependent distortion models and their calibration…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Xin Ma , Puchen Zhu , Xiao Li , Xiaoyin Zheng , Jianshu Zhou , Xuchen Wang , Kwok Wai Samuel Au

Universal photometric stereo (PS) is defined by two factors: it must (i) operate under arbitrary, unknown lighting conditions and (ii) avoid reliance on specific illumination models. Despite progress (e.g., SDM UniPS), two challenges…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Houyuan Chen , Hong Li , Chongjie Ye , Zhaoxi Chen , Bohan Li , Shaocong Xu , Xianda Guo , Xuhui Liu , Yikai Wang , Baochang Zhang , Satoshi Ikehata , Boxin Shi , Anyi Rao , Hao Zhao

Light microscopy is a widespread and inexpensive imaging technique facilitating biomedical discovery and diagnostics. However, light diffraction barrier and imperfections in optics limit the level of detail of the acquired images. The…

Quantitative Methods · Quantitative Biology 2026-03-24 Rui Li , Gabriel della Maggiora , Vardan Andriasyan , Anthony Petkidis , Artsemi Yushkevich , Mikhail Kudryashev , Artur Yakimovich

Remote sensing change detection is crucial for understanding the dynamics of our planet's surface, facilitating the monitoring of environmental changes, evaluating human impact, predicting future trends, and supporting decision-making. In…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Wele Gedara Chaminda Bandara , Nithin Gopalakrishnan Nair , Vishal M. Patel

We propose DiffuStereo, a novel system using only sparse cameras (8 in this work) for high-quality 3D human reconstruction. At its core is a novel diffusion-based stereo module, which introduces diffusion models, a type of powerful…

Computer Vision and Pattern Recognition · Computer Science 2022-07-21 Ruizhi Shao , Zerong Zheng , Hongwen Zhang , Jingxiang Sun , Yebin Liu
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